Part 3 of building a Python Chess Engine. Implement the move function for game simulation, encode move types, and filter out illegal moves.

Build a Strava heatmap using the Python API for custom GPS route visualization. Filter by type and date range for advanced data analysis.

Python chess engine development. Use bitboards and bitwise operations for efficient move generation for sliding and non-sliding pieces.

Beginner’s guide to the Strava API with Python. Use OAuth2 for authorization and get activity data. Handle access tokens and usage limits.

Learn K-Means Clustering for Image Segmentation in Python. Achieve color reduction and optimized performance using NumPy

Maximize chess engine speed with Python Bitboards. Use 1-Hot Encoding and bitwise operations to create an efficient board data structure.

Solve the Travelling Salesman Problem with a Genetic Algorithm. Learn selection, crossover, and mutation steps to find a near-optimal route.

The TSP is NP-Hard due to exponential complexity. Understand the time-accuracy trade-off in finding optimal vs. approximate routes.

The Genetic Algorithm uses Darwinian Evolution for machine learning. Learn selection, crossover, and mutation for efficient optimization.